Department of Psychology, University of Milano-Bicocca, Milan, Italy.
Department of Psychology, University of Milano-Bicocca, Milan, Italy.
Cogn Psychol. 2023 Sep;145:101594. doi: 10.1016/j.cogpsych.2023.101594. Epub 2023 Aug 18.
In the present study, we leveraged computational methods to explore the extent to which, relative to direct access to semantics from orthographic cues, the additional appreciation of morphological cues is advantageous while inducing the meaning of affixed pseudo-words. We re-analyzed data from a study on a lexical decision task for affixed pseudo-words. We considered a parsimonious model only including semantic variables (namely, semantic neighborhood density, entropy, magnitude, stem proximity) derived through a word-form-to-meaning approach (ngram-based). We then explored the extent to which the addition of equivalent semantic variables derived by combining semantic information from morphemes (combination-based) improved the fit of the statistical model explaining human data. Results suggest that semantic information can be extracted from arbitrary clusters of letters, yet a computational model of semantic access also including a combination-based strategy based on explicit morphological information better captures the cognitive mechanisms underlying human performance. This is particularly evident when participants recognize affixed pseudo-words as meaningful stimuli.
在本研究中，我们利用计算方法来探究在何种程度上，相对于直接从字形线索中获取语义，在诱导附加假词的意义时，额外利用形态线索是有利的。我们重新分析了一项关于附加假词词汇判断任务的研究数据。我们只考虑了一个通过词形到意义的方法（基于 n 元组）得出的语义变量（即语义近邻密度、熵、大小、词干接近度）的简约模型。然后，我们探讨了通过组合来自词素的语义信息（基于组合）得出的等效语义变量的添加在多大程度上提高了解释人类数据的统计模型的拟合度。结果表明，语义信息可以从任意字母组合中提取，但包含基于形态学信息的组合策略的语义获取计算模型更好地捕捉了人类表现背后的认知机制。当参与者将附加假词识别为有意义的刺激时，这一点尤为明显。
